In production industries, a product is generally inspected to ensure quality before it is distributed. Traditionally, such inspection is performed by a human, but it has been found that humans tend to have a high degree of failure due to distraction, illness and/or other circumstances. For this reason, many industries turn to machine vision to perform inspections of production goods. Machine vision is a useful alternative to human inspection when high speed, high magnification, 24-hour operation, and/or repeatable measurements are required.
As an example, wine makers use machine vision to inspect empty bottles for chips, cracks or other imperfections, as well as dirt and dust. They also use machine vision to verify the fill level and cork positioning of filled wine bottles, and to approve full cases of wine before they are released for distribution. Additionally, machine vision can be used to check the labels on wine bottles for both presence and placement.
The California wine industry produced 2.7 billion bottles of wine in 2005. Wineries' bottling lines currently produce up to 300 bottles per minute. Accordingly, it is necessary for winemakers to have an inspection system that not only successfully detects and rejects substandard product, but does so quickly and efficiently. Put another way, a machine vision imaging system used in any industry must not only identify defects, but must also keep up with demand placed on the system by the manufacturing line.
Conventional machine vision systems rely on mechanical stops or an orientation device to position and orient the product to be inspected so that the product is in a predetermined position. Orienting the product so that the positioning is known allows for a reduction in required processing power, but the time required to mechanically orient each product to be inspected imposes limitations on the potential throughput of the inspection system.